A Self-correcting Cooperative Spectrum Sensing for Cognitive Radio Networks in Low SNR Region

Within the domain of cognitive radio (CR), cooperative spectrum sensing (CSS) is employed to identify available spectrum bands for dynamic spectrum access, leveraging the spatial diversity of secondary users (SUs). However, the existing CSS methods have proven inadequate in effectively protecting the primary user (PU) from harmful interference, particularly in low signal-to-noise ratio (SNR) region. In this paper, we propose a self-correcting cooperative spectrum sensing (SC-CSS) by incorporating an error correction bit into each SU's sensing result. Under the proposed CSS mechanism, the PU's current state is determined by comparing the variation in the energy value of the received PU signal between the preceding and subsequent frames. Further, the closed-form expressions of the overall error probability of SC-CSS are also derived by analyzing a discrete Markov chain process and use it as a cost function in an optimization problem to find out the optimal sensing parameter. At last, numerical simulation results show the effectiveness and robustness of SC-CSS, establishing its superiority in CSS system operating under low SNR conditions.